This paper presents a generalized two-step maximum likelihood estimation method for partially identified vector autoregressive models. We suggest a likelihood ratio test for over-identification in a sub-system and derive the asymptotics for impulse responses and forecast-error variance...

This working paper presents a new coincident economic indicator developed by the COE, able to detect in real time peaks and troughs of the american business cycle. This probabilistic indicator is based on the Markov-Switching model proposed by Hamilton (1989), applied to various economic time...

In this paper we suggest a new technique to construct Markov processes by means of products of copula functions, in the spirit of Darsow et al, (1992). The approach requires to define: i) a sequence of distribution functions of the increments of the process; ii) a sequence of copula functions...

We estimate time varying risk sensitivities on a wide range of stocks' portfolios of the US market. We empirically test, on a 1926-2004 Monthly CRSP database, a classic one factor model augmented with a time varying specification of betas. Using a Kalman filter based on a genetic algorithm, we...

This paper surveys research on Emulative Neural Network (ENN) models as economic forecasters. ENNs are statistical methods that seek to mimic neural processing. They serve as trainable analytical tools that quot;learnquot; autonomously. ENNs are ideal for finding non-linear relationships and...

A univariate GARCH(p,q) process is quickly transformed to a univariate autoregressive moving-average process in squares of an underlying variable. For positive integer m, eigenvalue restrictions have been proposed as necessary and sufficient restrictions for existence of a unique mth moment of...

Motivated by a previous path-integral numerical algorithm for diffusion processes, PATHINT, we present a new tree algorithm, PATHTREE, an extremely fast accurate algorithm for developing probability distributions of general nonlinear Markovian-Gaussian diffusion processes

We generalize the functional form of the diffusion of the Black Scholes process and consider multi-factor models including stochastic volatility. Daily Eurodollar futures prices are fit to diffusions using methods of global optimization, Adaptive Simulated Annealing (ASA). These short-time...

We demonstrate that the volatility of Eurodollar options possesses its own volatility, and that this volatility of volatility appears to be a stochastic process. We give a theoretical approach to incorporate this stochastic volatility process into a generalization of the standard Black-Scholes...